Class/Object

ksb.csle.component.operator.cleaning

GeneralizedLinearRegressionOperator

Related Docs: object GeneralizedLinearRegressionOperator | package cleaning

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class GeneralizedLinearRegressionOperator extends BaseDataOperator[StreamOperatorInfo, DataFrame] with BaseDistanceCalculator

:: ApplicationDeveloperApi ::

Operator that performs Generalized Linear Regression. It generalizes linear regression by associating linear model with response variables that have error distribution models through link function and the magnitude of variance.

Linear Supertypes
BaseDistanceCalculator, BaseDataOperator[StreamOperatorInfo, DataFrame], BaseGenericOperator[StreamOperatorInfo, DataFrame], BaseGenericMutantOperator[StreamOperatorInfo, DataFrame, DataFrame], BaseDoer, Logging, Serializable, Serializable, AnyRef, Any
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Inherited
  1. GeneralizedLinearRegressionOperator
  2. BaseDistanceCalculator
  3. BaseDataOperator
  4. BaseGenericOperator
  5. BaseGenericMutantOperator
  6. BaseDoer
  7. Logging
  8. Serializable
  9. Serializable
  10. AnyRef
  11. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new GeneralizedLinearRegressionOperator(o: StreamOperatorInfo)

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    o

    Object that contains message ksb.csle.common.proto.StreamOperatorProto.GeneralizedLinearRegressionInfo GeneralizedLinearRegressionInfo contains attributes as follows:

    • familyType: Type of family. Enum(GAUSSIAN, BINOMIAL, POISSON, GAMMA) (required) GAUSSIAN: Data should be numeric (real or integer). BINOMIAL: Data should be binominal or polynominal with 2 classes. POISSON: Data should be numeric and non-negative (integer). GAMMA: Data should be numeric and continuous and positive(real or integer).
    • linkType: Type of link function which relates the linear predictor to the distribution function. Enum(IDENTITY, LOG, INVERSE, LOGIT, PROBIT, CLOGLOG, SQRT) (required)
    • maxIter: Maximum number of iterations. (required)

    GeneralizedLinearRegressionInfo

     message GeneralizedLinearRegressionInfo {
     required string labelName = 3
     required FamilyType familyType = 4 [default = GAUSSIAN];
     required LinkType linkType = 5 [default = IDENTITY];
     required int32 maxIter = 6;
     enum FamilyType {
         GAUSSIAN = 0;
         BINOMIAL = 1;
         POISSON = 2;
         GAMMA = 3;
     }
    enum LinkType {
         IDENTITY = 0;
         LOG = 1;
         INVERSE = 2;
         LOGIT = 3;
         PROBIT = 4;
         CLOGLOG = 5;
         SQRT = 6;
     }
     }

Value Members

  1. final def !=(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

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    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  4. def ManhattanDistanceMetric(x: Row, y: Row): Double

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    Definition Classes
    BaseDistanceCalculator
  5. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  6. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  7. final def eq(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  8. def equals(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  9. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  10. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  11. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  12. final def isInstanceOf[T0]: Boolean

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    Definition Classes
    Any
  13. val logger: Logger

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    Attributes
    protected
    Definition Classes
    Logging
  14. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  15. final def notify(): Unit

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    Definition Classes
    AnyRef
  16. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  17. def operate(df: DataFrame): DataFrame

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    Operates GeneralizedLinearRegression.

    Operates GeneralizedLinearRegression.

    df

    Input dataframe

    returns

    DataFrame Output dataframe

    Definition Classes
    GeneralizedLinearRegressionOperator → BaseGenericOperator → BaseGenericMutantOperator
  18. val p: GeneralizedLinearRegressionInfo

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  19. def stop: Unit

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    Definition Classes
    BaseGenericOperator → BaseGenericMutantOperator
  20. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  21. def toString(): String

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    Definition Classes
    AnyRef → Any
  22. def validate(df: DataFrame): Unit

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    Validates GeneralizedLinearRegression info and dataframe schema info using following params.

    Validates GeneralizedLinearRegression info and dataframe schema info using following params.

    Annotations
    @throws( classOf[KsbException] )
  23. final def wait(): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  25. final def wait(arg0: Long): Unit

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from BaseDistanceCalculator

Inherited from BaseDataOperator[StreamOperatorInfo, DataFrame]

Inherited from BaseGenericOperator[StreamOperatorInfo, DataFrame]

Inherited from BaseGenericMutantOperator[StreamOperatorInfo, DataFrame, DataFrame]

Inherited from BaseDoer

Inherited from Logging

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

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